from vocab import Vocabulary
import evaluation
data_path = '/data/yangy/xuyc/data1/data'
import torch
device = torch.device("cuda: 5" if torch.cuda.is_available() else "cpu")

# evaluation.evalrank("./runs/coco_scan/log/model_best.pth.tar", device=device, data_path=data_path, split="test", fold5=False)
evaluation.evalrank("./runs/coco_scan/log/model_best.pth.tar", device=device, data_path=data_path, split="test", fold5=False)

"""
TextModel
- feature_encoder: output:b, cls_num*10
- pos_encoder: b, cls_num*10
- TransformerModel: b, 
- loss: 
"""
